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OPTIMAL CONTROL OF BIOLOGICAL INVASIONS IN LAKE NETWORKS

2007· article· en· W2013410297 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNatural Resource Modeling · 2007
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsMetapopulationInflowOutflowControl (management)EcologySimple (philosophy)Moment (physics)EcosystemLimitingOperations researchComputer scienceEnvironmental scienceGeographyMathematicsBiologyEngineeringPhysicsMeteorologySociologyArtificial intelligence

Abstract

fetched live from OpenAlex

ABSTRACT. A metapopulation model for alien species invasion of a lake network is coupled with an economic model of prevention. The model restates a stochastic problem in deterministic terms. It provides a macroscopic description of the lake network with prevention methods controlling both the outflow of invaders at infected lakes and the inflow of invaders at uninfected lakes. Results indicate that optimal control implements no more than one of these methods at any moment in time. Typical optimal control measures change over time as the lake ecosystem becomes successively more invaded. Early control of outflow from infected lakes is replaced by later control of inflow to remaining uninfected lakes. Closed‐loop control trajectories are analytically characterized in the phase‐plane for a limiting case, while in general a simple and stable numerical algorithm is developed for solving the optimal control problem. This research has been supported by a grant from the National Science Foundation (DEB 02–13698). The second author acknowledges support from Canada Research Chair, an NSERC Collaborative Research Opportunity grant, and an NSERC Discovery grant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.305
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it